Repository to keep track of plans, tools, decisions and ways to make things.
workspace/ ├── analysis/ # Training and model development │ ├── attribution/ # Attribution methods │ │ ├── captum_attribution.py # Feature attribution via Captum │ │ ├── dac_computation.py # Decision Attribution Computation (DAC) │ │ ├── mask_dataset_creation.py # Generate masks & create new datasets │ ├── classifier/ # Classifier models │ │ ├── classifier_architecture.py # Classifier model definition │ │ ├── classifier_lightning.py # Lightning version of classifier │ │ ├── classifier_metrics.py # Validation metrics computation │ │ ├── classifier_training.py # Classifier training logic │ ├── gan/ # Generative models │ │ ├── generative_architecture.py # GAN/VAE model definition │ │ ├── generative_lightning.py # Lightning version of generative model │ │ ├── generative_metrics.py # Generative model metrics │ │ ├── generative_training.py # Generative model training script │ ├── marimo/ # Visualization tool integration │ │ ├── marimo_interface.py # Interface for MARIMO │ ├── custom_dataset.py # Custom dataset definition │ ├── data_splitting.py # Logic for train-test split ├── configs/ # Configuration files (optional) │ ├── dataset_config.yaml # Dataset selection configurations │ ├── model_config.yaml # Hyperparameters & model settings ├── datasets/ # Datasets │ ├── images/ # Zarr folder (real, fake) │ ├── metadata/ # Sample metadata from dataset_retrieval │ ├── profiles/ # Raw cell-profiler features ├── dataset_retrieval/ # Data selection and preprocessing │ ├── balance_dataset.py # Balancing dataset script │ ├── image_retrieval.py # Image retrieval & cropping script │ ├── plot_utils.py # Plotting utilities │ ├── select_jump_dataset.ipynb # Notebook for JUMP dataset selection & mAP computation ├── figures/ # Figures and plots │ ├── attribution_maps/ # Captum feature attributions │ ├── generated_samples/ # Generated samples from models │ ├── image_filtering/ # Image filtering for cell detection